Surgery Scheduling Under Case Cancellation and Surgery Duration Uncertainty

Pang, Bowen; Xie, Xiaolei; Song, Yongjia; Luo, Li

doi:10.1109/tase.2018.2834486

Cited by 20 publications

(10 citation statements)

References 35 publications

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“…Constraint (12) states that for common patients who have undergone an operation, the waiting time to receive recovery services should be less than the fixed value. Constraint (13) states that if two patients in a ward ask to receive equipment, only one of the patients receives treatment and the other patient is put in the queue. Constraint (14) states that if a patient is in the queue before another patient, they wait until that specific equipment will be unused.…”

Section: Indicesmentioning

confidence: 99%

“…Here, to verify the applicability of the proposed algorithms, the aforementioned metrics are applied to the considered test problems. These 12 test problems are divided into small-sized (1-4), medium-sized (5-8), and large-sized (9)(10)(11)(12)(13)(14)(15).…”

Section: 3 Metrics For Comparing Algorithmsmentioning

confidence: 99%

“…The operating room, especially surgical room has a particular sensitivity [11] and is considered as the most vital unit in medical centers [12]. Therefore, the smallest defect or non-compliance with a specific planning and pre-determined standards will cause problems [13]. According to the above-mentioned discussion, operating room can be likened to medical center engine [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Maghzi

Mohammadi

Pasandide

et al. 2022

IJE

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T oday, planning and scheduling problems are the most significant issues in the world and make a great impact on improving organizational productivity and serving systems such as medical and healthcare providers. Since operating room planning is a major problem in healthcare organizations, the optimization of medical staff and equipment plays an essential role. Thus, this study presents a multiobjective mathematical model with a new categorization (preoperative, intraoperative, and postoperative) to minimize operating room scheduling and the risk of using equipment. Time constraints in healthcare systems and medical equipment limited capacity are the most significant considered limitation in the present study. In this regard, since the duration of patient preparation and implementation of treatment processes occur in three states of optimistic, pessimistic, and normal, the introduced parameters are examined relying on a fuzzy uncertainty analysis of the problem. Hence, the model is measured in a real numerical solution sample in a medical center to evaluate and confirm the proposed mathematical model. T hen, two meta-heuristic algorithms (NRGA and NSGAII) are implemented on the mathematical model to analyze the proposed model. Finally, the research results indicate that the NSGA-II is more efficient in the operating room scheduling problem.

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Section: Indicesmentioning

confidence: 99%

Section: 3 Metrics For Comparing Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Maghzi

Mohammadi

Pasandide

et al. 2022

IJE

View full text Add to dashboard Cite

show abstract

“…The constraints were collected and included into the analysis which results in the automated schedule provide fairness and more effective among the physicians [17]. In the research of [18], a stochastic integer programming was developed for multiple operating room to minimize the costs from both health care providers and patients. Synthetic data was used to test the performance of the proposed model and experiments were conducted to show the effectiveness of the proposed model.…”

Section: Schedulingmentioning

confidence: 99%

Review on Queueing Problem in Healthcare

Ariff¹,

Kamardan²,

Sufahani³

et al. 2018

IJET

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This article shows the application of queueing, simulation and scheduling used in the field of healthcare. A summary of queueing, simulation and scheduling theory used in waiting time, appointment system and patient flow are summarised in this article. Different departments in the healthcare system are also considered in this article such as emergency department, outpatient department and the pharmacy. The aim is to provide the reader a general background into queueing, simulation and scheduling in the healthcare.

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“…Numerous works have used stochastic programming to model the uncertain surgery durations in the OR scheduling problems [1], [7], [25], [32]. The majority of these models consider optimizing the expectation of costs/revenues during the planning horizon [10].…”

Section: Introductionmentioning

confidence: 99%

A Decomposition Algorithm for the Two-Stage Chance-Constrained Operating Room Scheduling Problem

Najjarbashi

Lim

2020

IEEE Access

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The required time for surgical interventions in operating rooms (OR) may vary significantly from the predicted values depending on the type of operations being performed, the surgical team, and the patient. These deviations diminish the efficient utilization of OR resources and result in the disruption of projected surgery start times. This paper proposes a two-stage chance-constrained model to solve the OR scheduling problem under uncertainty. The goal is to minimize the costs associated with OR opening and overtime as well as reduce patient waiting times. The risk of OR overtime is controlled using chance constraints. Numerical experiments show that the proposed model provides a better trade-off between minimizing costs and reducing solution variability when compared to two existing models in the literature. It is also shown that the three models converge as the overtime probability threshold approaches one. Moreover, it is observed that the individual chance constraints result in the opening of fewer rooms, lower waiting times, and shorter solution times when compared to that of joint chance constraints. A decomposition algorithm is applied that solves large test instances of the OR scheduling problem, that of which is known to be NP-hard. Strong valid inequalities are derived in order to accelerate the convergence speed. The proposed approach outperformed both a commercial solver and a basic decomposition algorithm after solving all test instances with up to 89 surgeries and 20 ORs in less than 48 minutes. INDEX TERMS Chance constraints, mixed-integer programming, operating room scheduling, two-stage stochastic programming, uncertainty.

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Surgery Scheduling Under Case Cancellation and Surgery Duration Uncertainty

Cited by 20 publications

References 35 publications

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Review on Queueing Problem in Healthcare

A Decomposition Algorithm for the Two-Stage Chance-Constrained Operating Room Scheduling Problem

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